With the progress of technology and the development of social economy, people's demand for indoor positioning services is increasing continuously; in some public places, such as markets, airports, exhibition halls, office buildings, warehouses, underground parking garages, and so on, accurate indoor positioning information can help a user shop, travel, find out an indoor target, and do the like; can achieve highly efficient management of available space and material stock, and can direct policemen, firemen, soldiers, or health care workers, and the like to accomplish specific indoor tasks. Intelligent space, pervasive computing and the like cannot work without location services, therefore, indoor positioning has a broad application prospect. Although GPS (Global Positioning System) can meet the requirements of many applications in the aspect of outdoor positioning, due to the obstructions by walls and indoor objects, in an indoor environment, GPS signals may be very weak or even disappear, therefore, it is difficult to use GPS to perform positioning indoors.
Domestic and abroad researches in indoor positioning technologies are quite abundant. According to positioning principles, a proximity detection method, a fingerprint matching method, a multilateration/angulation method, and so on, can be provided. The proximity detection method uses the place of a detected signal source as the locating position, and has a low accuracy. The fingerprint matching method uses signal characteristics in the indoor environment to match position and can obtain a better positioning accuracy, however, the result may be easily affected by the multipath effect, environment changes, and so on, and thus the positioning result may not be stable, with limited accuracy; moreover, a fingerprint database may need to be established, and cumbersome work is required. The multilateration/angulation method needs to use an algorithm, such as TOA (Time of Arrival), TDOA (Time Difference of Arrival), and AOA (Angle of Arrival), to accurately measure information such as distance/angle from a positioning point to a reference point firstly, and then use a positioning method, such as a trilateration method, to position a target. If the location information of the reference point is accurate, and the measured distance is accurate too, a location of a target node can be calculated accurately; however, in reality, these measurements may contain errors, which affect the positioning results. If full indoor signal coverage is required, many reference points need to be provided, thereby making the cost very high.
A patent application with an application number of CN201110054768.3 discloses a weighted trilateration positioning method based on RSSI (Received Signal Strength Indicator), of which the limitation is that this method cannot accurately measure the distance between nodes, and thus the position error is large.
A patent application with an application number of CN201210290193.X discloses a WLAN (Wireless Local Area Network) indoor positioning method based on matrix relations, of which the limitation is that collecting indoor environment characteristic fingerprints needs much manpower and material resources, and due to the complexity of the indoor environment which causes serious multipath effect, wireless signals are adversely affected, so that the positioning accuracy is low.